| Project/Area Number |
20500093
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Media informatics/Database
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| Research Institution | Osaka University |
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Principal Investigator |
HARA Takahiro Osaka University, 大学院・情報科学研究科, 准教授 (20294043)
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| Co-Investigator(Kenkyū-buntansha) |
NAKAYAMA Kotaro 東京大学, 知の構造化センター, 特任助教 (00512097)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2009: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2008: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
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| Keywords | 人工知能 / 情報システム / 情報検索 / ソーシャルメディア / 連想検索 / スケーラビリティ / Wikipedia / データベース |
|---|
| Research Abstract |
Social media systems allow users to construct contents collaboratively on the Web. Because of the unique characteristics such as coverage and accuracy, it has become one of the promising corpora for knowledge extraction. However, there exist two major technical issues on social media analysis ; scalability and credibility. In this research project, to solve these problems, we have conducted a series of research ; 1) scalable association extraction, 2) machine learning for finding important features, 3) a large scale test collection construction and 4) integrated analysis across different types of resources.
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